A stochastic daily mean temperature model for weather derivatives
This research provided an in depth statistical analysis of the daily mean temperature time series for eighteen cities from the Chicago Mercantile Exchange (CME). The residuals, which represented the difference between the observed data and trend, were used to develop two models to simulate a possible temperature time series for 2007. A distribution of ten thousand possible outcomes were created for each model, and then analyzed against the climatologic data sets. Ultimately, this research exhibited that statistics extracted from the analysis of the residuals could be simulated to produce realistic outcomes of degree days for weather derivative contracts.